Compressing AI Models (LLMs) using Distillation, Quantization, and Pruning
1:12
YouTubeRajistics - data science, AI, and machine learning
Compressing AI Models (LLMs) using Distillation, Quantization, and Pruning
A couple of techniques we use to compress models. This saves GPU memory and can reduce the amount of compute needed. Model distillation compresses a large model’s knowledge into a smaller one, quantization reduces memory usage by representing parameters with fewer bits, and pruning streamlines the model by removing less important weights ...
2.9K viewsFeb 2, 2025
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Microsoft and CMU researchers have begun to unravel three mysteries in deep learning related to ensemble, knowledge distillation, and self-distillation. Discover how their work has led to the first theoretical proof with empirical evidence for ensemble in deep learning: https://aka.ms/AAavuq3 | Microsoft Research
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Microsoft and CMU researchers have begun to unravel three mysteries in deep learning related to ensemble, knowledge distillation, and self-distillation. Discover how their work has led to the first theoretical proof with empirical evidence for ensemble in deep learning: https://aka.ms/AAavuq3 | Microsoft Research
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